Reliance on Feelings in Information Processing: How Relying on Your Gut Feeling Can Lead to Illusory Pattern Perception

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Reliance on Feelings in Information Processing:

How Relying on Your Gut Feeling Can Lead to Illusory

Pattern Perception

Master Thesis for MSc. Marketing

by Regina Klitsie

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Reliance on Feelings in Information Processing: How Relying on Your Gut Feeling Can Lead to Illusory Pattern perception

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A Thesis Presented to the Marketing Department of The Faculty of Economics and Business University of Groningen

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In Partial Fulfillment of the Requirements for the Degree Master of Science in Marketing _____________ by Regina Klitsie +31624327575 r.s.klitsie@student.rug.nl S3845249 _____________ Supervisor: Dr. A. Schumacher Second Assessor: Dr. J.P.R. Thomassen

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Management Summary

Social psychology and consumer research suggest that affect has a more dominant role in decision-making and judgments than reasoning. In other words, consumers rely more on their feelings in deciding and judging. Previous research has mostly found positive consequences of reliance on feelings in decision-making and forming judgments. The negative impact is, however, less known.

In this research, it is proposed that, when an individual relies on his/her feelings, this person taps into the default mode of the brain, and he/she engages in the affectively cued, unconscious, and effortless “System 1 thinking”. As the brain’s default mode and System 1 thinking are linked to unconscious associative processes that are based on experience, it can be concluded that a feeling-based mindset (compared to a reasoning-based mindset) is related to establishing links in the mind. Finally, it was found that emotional experiences can fortify illusory patterns. Therefore, it is proposed that reliance on feelings can cause individuals to fall for illusory pattern perception: they are more likely to spot a coherent and meaningful interrelationship among a set of random or unrelated stimuli. In addition, it is expected that this effect is stronger for people who possess the cognitive trait of preference for consistency, as these people aim to maintain congruence in their actions and are thus more likely to perceive more illusory patterns.

In order to test these assumptions, an online survey has been executed amongst 202 respondents. The survey consisted of a task that either effectuated a feelings-based mindset, or a reasoning-based mindset, a task to measure illusory pattern perception, a scale to measure the level of preference for consistency, and a measure of cultural background in order to control for differences in responses between people from Eastern and Western cultures.

Analysis indicated that there is indeed a positive relationship between reliance on feelings and illusory pattern perception, and cultural background has an influence on this effect. However, a moderating effect of preference for consistency was not found.

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and seeing imaginary figures. Marketing efforts should then be adapted in order to manipulate consumers into a more analytic, reasoning-based mindset.

Additionally, when consumers use affect as information in, for example, deciding whether to go to a certain store, this might have a negative outcome. If a consumer has previously had a bad experience at that specific store, he/she might be reluctant to return, as this person is then more likely to believe that a subsequent visit might be another poor experience.

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Preface

This thesis concerns the effect of relying on feelings in decision-making and forming judgments on illusory pattern perception. It is a culmination of my Master Marketing study at the University of Groningen. I was engaged in executing research and writing this thesis from February to June 2020.

The process was difficult at times, and an extensive amount of time and effort was put into it. Conducting substantial research into previously developed theories and executing an online survey with 202 participants allowed me to establish an answer to my hypotheses, and to fulfill the purpose of my research.

The project has been executed by myself, but with the support and help of many people in my network. Firstly, I would sincerely like to thank my thesis supervisor, Dr. A. Schumacher, for guiding me through the process of writing my thesis. Fortunately, she was always willing to answer any questions I had.

Secondly, I would like to thank all the people in my network who have contributed to my research by filling out the online survey. Without their collaboration, it would not have been possible to conduct this analysis. I would also like to thank the people who have shared my survey through different social media platforms and with their own networks.

I hope you enjoy reading my research. Regina Klitsie

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1. Introduction

People make decisions based on beliefs about processes, objective states, and events, combined with desires (e.g., personal goals, values and utilities). This is known as cognitive orientation, which has been the foundation of human behavior and decision making in various disciplines. However, this human behavior and decision making cannot only be based on cognition-oriented theories. Social psychology and consumer research suggest that “affect plays a more central role” in the process of decision making (Kim, Chan, & Chan, 2007, p. 513).

In general, behavioral sequences contain both cognitive and affective components. In order to make decisions that lead to certain goals, cognitive activity is needed. But this process is controlled, interpreted and accompanied by affective states. Often, consumers make choices based on affective feelings, whether they are prompted by the chronic tendencies of the decision maker, by product characteristics, or by the marketer’s advertising campaign (Chang & Hung, 2018). Research in several areas has indicated that feelings should be included in studying human behavior with regards to consumer decision-making (Kim et al., 2007).

The affect-as-information model helps in understanding how feelings are used by consumers in guiding their decisions. It states that, in evaluating targets, people may hold the representation of the target in their minds and ask themselves how they feel about it (Schwarz & Clore, in Pham, 1998). Consequently, this information functions as “a basis for judgments and decisions” and as “a guide for cognitive processing” (Storbeck & Clore, 2008, p. 1824). In this process, feelings are used as sources of information and individuals rely on them.

This reliance on feelings has an impact in several domains. For example, Lee, Amir and Ariely (2009) found that relying on feelings has a positive subsequent effect on cognitive noise, which they define as the greater susceptibility of the cognitive system to decisional noise. Additionally, Pham, Lee and Stephen (2012) argue that individuals have improved skills in predicting the outcome of future events when they have higher levels of trust in their feelings (compared to individuals low in trust in feelings), which they call the “emotional oracle effect”. Furthermore, Pham, Cohen, Pracejus and Hughes (2001) found that judgmental responses are, importantly, more prophetic of the amount and valence of people’s thoughts. Also, they are more consistent and stable across individuals, and potentially faster.

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and forming judgments; thus, that reliance on feelings can also have a negative influence. It is proposed that, when an individual relies on his or her feelings, this may lead to recognizing connections that are actually non-existent: the likelihood to detect patterns in random information increases - also referred to as “illusory pattern perception”. It is defined as “the identification of a coherent and meaningful interrelationship among a set of random or unrelated stimuli (such as the tendency to perceive false correlations, see imaginary figures, form superstitious rituals, and embrace conspiracy beliefs, among others)” (Whitson & Galinsky, 2008, p. 115).

It is expected that, when an individual relies on feelings in deciding and judging instead of on reasoning, this person engages in implicit cognitive processing, which is automatic, heuristic, unconscious and spontaneous (Haeffel, Abramson, Brazy, Shah, Teachman, & Nosek, 2007). It is argued that, when a person relies on feelings, he or she taps into the default mode of the brain, and he or she engages in the affectively cued System 1 thinking. As the brain’s default mode and System 1 thinking are linked to unconscious, associative processes that are based on experience, it can be concluded that a feeling-based mindset (compared to a reasoning-based mindset) is related to establishing links in the mind.

In addition, it was found that emotional experiences, feelings of lacking control, and an intuitive (compared to analytical) thinking style have a strengthening effect on imagined patterns (Mattson, 2014; Whitson & Galinsky, 2008; Walker, Turpin, Stolz, Fugelsang, & Koehler, 2019). Therefore, it is proposed that reliance on feelings can effectuate illusory pattern perception.

Furthermore, Guadagno, Asher, Demaine and Cialdini (2001) state that an individual might have PFC as a character trait. People scoring high in this aspect value personal consistency and they are highly focused on aligning their responses in almost all situations with their past attitudes, actions and commitments. Therefore, it is argued that individuals are more likely to engage in illusory pattern perception when they have a higher PFC compared to a person with low PFC, as these people seek for consistency in their actions.

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From a managerial point of view, this study is important in guiding Marketing managers in their communications with consumers, and whether they should manipulate reliance on feelings, or reliance on reasoning in their marketing efforts.

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2. Theoretical Framework

The concept in this paper consists of the following variables: reliance on feelings, PFC, and illusory pattern perception.

2.1 The Brain’s Default Network Mode and Associative Processing

When our mind is not engaged in goal-directed tasks, our brain is “resting”. This is called the default mode (Bar, Aminoff, Mason, & Fenske, 2007). Activity within this default mode network is related to associative processing: this is what our brain is busy with most often. Associative thinking can be regarded as the foundation of thought. During our brain’s resting times, numerous processes occupy our minds, such as planning future actions, contemplating, simulating possible scenarios, replaying past events, memory consolidation and fantasizing. It is argued that the majority of the aforementioned processes, if not all, are depending on “the activation of experience-based associations” (Bar et al., 2007, p. 420). Thus, when our brain is in default mode, it is engaged in associative processing.

Aminoff and Tarr (2015, p. 2) state the following regarding associative processing: “What we mean by associative is that the features of any kind of mental representation, irrespective as to whether that representation is nominally visual, linguistic, etc., are related to one another via learned associations”. It is argued by Mattson (2014) that superior pattern processing (SPP) is the foundation of most, or even all of our brain’s unique features, including language, intelligence, invention, imagination, and believing in imaginary entities like gods and ghosts. Furthermore, he argues that SPP is involved with the neuronal network-based, electrochemical, integration, encoding and transfer of mentally fabricated or perceived patterns to other individuals. These capabilities in pattern processing have become increasingly sophisticated during human evolution, because the cerebral cortex has expanded. In particular, the prefrontal cortex, and regions in the brain that are involved in image processing (Mattson, 2014).

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2.2 The Brain’s Default Mode and Emotions

The experience-based associative representations that are stored in the brain’s default mode (Bar et al., 2007) form the foundation of affective predictions. These associative representations “mediate the brain’s ability to generate predictions about which other objects and events to expect in a given context” (Shenhav, Barrett, & Bar, 2012, p. 47). When people rely on their feelings in decision-making, they base it on experience-based associations: they thus tap into their brain’s default mode.

This is related to System 1 thinking. In order to make a distinction between fast and slow thinking, System 1 and System 2 thinking were established (Kahneman, 2011). The former is related to thinking fast and the latter to thinking slowly. The affectively cued System 1 is automatic, intuitive, effortless, gullible, heuristic, and unconscious. Additionally, this system can answer questions in a fast way through resemblances and associations. It includes memory, perception, unconscious attention, automatic causal narratives, and also emotion. Generally, System 1 can be explained as a reflex system, which is linked to pattern perception, and by which an automated thinking mode is triggered (Tay, Ryan, & Ryan, 2016). System 1 thinking can also be described as implicit processing, which is characterized by “processes that are guided by the automatic activation of stable memory constructs, occur without intention or effort, and do not tax cognitive resources” (Haeffel et al., 2007, p. 1156). When a person depends on System 1, when s/he is angry or tired for example, decision-making might be heavily affected in accuracy (Tay et al., 2016). On the contrary, System 2 is slow, conscious, controlled, effortful, deliberate and statistical.

Thus, the brain’s default mode and System 1 are highly related. Both are characterized by cognitive ease: System 1 thinking reflects cognitive ease, as it is characterized by effortless, fast thinking, and the brain’s default mode reflects spontaneous cognition (Gronchi & Giovannelli, 2018). Additionally, as stated before, both are based on associative processing. 2.3 The Influence of Affect on Judgments, Decisions, and Cognitive Processes

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It has already been established in previous research that relying on feelings has an influence on forming judgments and making decisions. In the past three decades, many studies have shown that affective feelings can substantially influence many types of judgments. For example, the affect-as-information model states that, in evaluating targets, people may hold the representation of the target in their minds and ask themselves how they feel about it (Pham, 1998). In this process, feelings are used as sources of information. For example, when a consumer wants to decide whether he or she should go to the mall to go clothes shopping, the consumer may hold in his or her mind a representation of this event and see “how it feels”. A positive evaluation would be created by positive feelings about the event, whereas a negative evaluation would be based on unfavorable feelings. This process is called the “How-do-I-feel-about-it?” heuristic (Schwarz & Clore, in Pham, 1998). The model states that arousing, pleasant and unpleasant reactions provide experiential and bodily information about the positive and negative value of what is encountered, and the importance of it. Consequently, this information functions as “a basis for judgments and decisions” and as “a guide for cognitive processing” (Storbeck & Clore, 2008).

Furthermore, it was found by Lee et al. (2009) that relying on feelings has a positive subsequent effect on cognitive noise: if an individual relies more heavily on his/her feelings during making decisions, he or she will experience reduced cognitive noise. Additionally, Pham et al. (2012) argue that individuals have improved skills in predicting the outcome of future events when they have higher levels of trust in their feelings (compared to individuals low in trust in feelings), which they call the “emotional oracle effect”.

Monitoring feelings consciously leads to potentially faster judgmental responses that are also more predictive of the valence and number of individuals’ thoughts, and more consistent and stable across individuals (Pham et al., 2001).

Based on the aforementioned impact of relying on feelings on decision-making, forming judgments, and cognitive processes, it can be concluded that relying on feelings as information has an obvious role in the formation of these processes.

2.4 Illusory Pattern Perception

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beliefs, among others)” (Whitson & Galinsky, 2008, p. 115). It occurs when people incorrectly perceive stimuli as causally determined through a nonrandom process, while in fact the stimuli are randomly generated. Consequently, they perceive it as diagnostic for which future stimuli they can expect. An example of illusory pattern perception is when players and spectators in a basketball game believe that the chance of a successful shot by a player is connected to the success of the previous shot. However, in reality, the correlation between misses and hits of successful shots from that player did not deviate statistically from chance (van Prooijen, Douglas, & De Inocencio, 2017).

It was found that individuals who feel like they lack control are more inclined to restore feelings of control and therefore are more likely to perceive various illusory patterns (Whitson & Galinsky, 2008). When an individual is not able to objectively gain a sense of being in control, he or she attempts to gain control perceptually by perceiving meaningful interrelationships between unrelated stimuli - they perceive illusory patterns. Through experiments, Whitson and Galinsky (2008) found that taking away the sense of control led the participants to perceive figures in meaningless static, to have an increased need for structure, and to believe in a cause and effect relationship in unconnected, random behaviors.

Additionally, it is argued that if someone engages in an intuitive thinking style, which is the opposite of an analytic thinking style, this person is more likely to see patterns in random noise, and to endorse illusory patterns and irrational beliefs (Walker et al., 2019).

2.5 Linking Reliance on Feelings to Illusory Pattern Perception

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Thus, based on the aforementioned information, I argue that reliance on feelings has a positive influence on illusory pattern perception. My first hypothesis is formulated as:

H1: Reliance on feelings (compared to reliance on reasoning) increases illusory pattern perception.

2.6 Preference for Consistency

Guadagno et al. (2001) state that, when a person has PFC, he or she prefers to behave consistently with previous attitudes and behaviors. This personality trait entails “(1) the motive to be consistent with one’s own responses, (2) the desire to appear consistent to others, and (3) the desire that others appear consistent” (Heitland & Bohner, 2010, p. 165).

Cialdini, Trost and Newsom (1995) state that people who have a high PFC value personal consistency and they are highly focused on aligning their responses in almost all situations with their past attitudes, actions and commitments. On the other hand, individuals who have a low PFC seem to prefer change, unpredictability, and spontaneity in their responses rather than congruence with their previous responses. Guadagno et al. (2001) also concluded from their research that individuals high (low) in PFC likely become more (less) consistent with a certain action when they focus on the personal implications of it.

Based on the aforementioned characteristics of PFC, it can be assumed that people who have a high PFC are more prone to fall for illusory pattern perception when they rely on their feelings, as they seek for consistency in their actions. This means that, when they rely on their feelings in making a decision or in forming a judgment, they will likely continue this behavior in their subsequent actions. Furthermore, as already stated, a person falls for illusory pattern perception when he or she thinks that the chance of something happening is connected to whether it has happened before, and it can thus be assumed that a person with high PFC will likely be even more prone to base the chances of something happening on the outcome of past events. Therefore, the second hypothesis is formulated as follows:

H2: PFC positively moderates the relationship between reliance on feelings and illusory pattern perception.

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1 thinking are linked to unconscious associative processes that are based on experience, it can be concluded that a feeling-based mindset (compared to a reasoning-based mindset) is related to establishing links in the mind. Finally, it was found that emotional experiences, feelings of lacking control, and an intuitive thinking style can fortify illusory patterns. Therefore, it is proposed that reliance on feelings can cause an individual to spot a coherent and meaningful interrelationship among a set of random or unrelated stimuli. Additionally, it is argued that individuals are more likely to engage in this illusory pattern perception when they have a higher PFC compared to a person with low PFC, as they seek for consistency in their actions.

Based on the hypotheses, the following conceptual model is created:

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3. Research Design

3.1 Participants

The sample size in this research was 250. However, after exclusion of 48 participants, based on several criteria that are discussed in section 3.2, my population size was 202.

Of the 202 participants, 89 were male (44%) and 113 were female (56%) (Mage = 25.94,

SDage = 6.40), where the minimum age was 16, and the maximum age 56. Additionally, 85 participants had an Eastern cultural background (42%), and 117 participants had a Western cultural background (58%).

A Chi-Square analysis was conducted to test whether there were significant differences between the two conditions (reason-based mindset and feeling-based mindset) in terms of cultural background, gender, and age. Chi-Square analysis is used when group differences of categorical variables need to be analyzed (McHugh, 2013). A new variable was created for age, with two categories (below average age and above average age), as Chi-Square analysis should only be used with categorical variables.

The results of the Chi-Square analysis can be found in Appendix 1.

As can be seen from the output, there were no significant differences between both conditions in terms of cultural background, X2_{(1, N = 202) = .00, p = .958. Additionally, no}

significant differences could be found in gender, X2_{(1, N = 202) = .01, p = .941, and also not in}

age X2_{(1, N = 202) = .00, p = .997.}

Furthermore, a Non-Parametric Chi-Square One-Sample Test was conducted in order to analyze the differences between the observed and expected frequencies of the two categories of the reliance on feelings variable. The results are shown in Appendix 2, and the output shows there were no significant differences between both conditions X2_{(1, N = 202) = .317, p = .574.}

In the dataset of 250 respondents in total, 28 cases were excluded from the analyses for failing the attention check that is discussed in section 3.2, two respondents were excluded because they experienced technical issues, and two participants were excluded as they simultaneously had technical issues and failed the attention check. Additionally, nine participants were excluded that stated they were neither from a Western or Eastern culture, or that refused to respond to this question. This is elaborated in section 3.2.

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be excluded. It is decided based upon the mean and standard deviation of the condition the outlier occurs in, as it is a criterium to exclude participants by condition. In Appendix 3, the calculations are shown that were executed in order to decide which cases were outliers.

In total, 48 respondents were excluded, as it can be assumed that they were biased in their responding behavior, either because of a lack of attention, or because of technical issues during the survey. Thus, data analysis was executed with 202 respondents.

3.2 Measures

In order to test the hypotheses in this research, an experiment in the form of an online survey is executed. Thus, the data collection is conducted through quantitative research.

The independent variable in this research is reliance on feelings. The survey contained items with which the independent variable was manipulated. Using the manipulations that were also executed by Chang and Hung (2018), two conditions were included in the beginning part of the survey. Each participant was randomly assigned to one of the two conditions in a one factor (Reliance on feelings: Low, High) between-subjects design. Additionally, it is essential to mention that everything but the manipulation was kept constant in order to keep cognitive load at the same level. In other words, the load imposed by the task on the participants’ cognitive system (Paas & van Merriënboer, 1994) should be the same for both conditions. Thus, the text that was shown beforehand was the same length for each condition.

After the independent variable manipulation, a task was included that measured the dependent variable in this research: illusory pattern perception. This task, which is called the ‘Snowy Pictures Task’ (SPT), has been executed before in research by Whitson and Galinsky (2008). In the original task, the participants were shown 24 snowy pictures in total, of which 12 contained a hidden picture, and the other 12 were static, which means they did not contain a hidden picture. However, in my online survey, the number of pictures in the task was reduced in order to prevent the survey from becoming too extensive and to retain the attention of the participants. Ten pictures were shown in total, of which five were static and five contained a hidden picture (see Appendix 4). Pictures 1, 3, 4, 5 and 6 contained a hidden picture; thus, pictures 2, 7, 8, 9 and 10 were the static pictures. The five static pictures were used to measure the dependent variable of illusory pattern perception. The five pictures that contained a hidden picture measured true pattern perception and were used for an additional analysis.

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10 = ‘I clearly see a pattern’. When participants selected five or higher on the scale, they were asked to indicate what they saw in that picture.

The moderator in this research is PFC, which was measured using a scale that was developed by Cialdini, Trost and Newsom (1995). They have concluded that PFC is a personality trait that is measurable, and they have established a valid instrument for assessment of it: the PFC Scale. It helps with measuring the variation in the longing for being consistent and also to be seen like it. Therefore, the moderator was included in the survey as an individual difference measure. The PFC Scale can be found in Appendix 5 and was measured using a scale from one to nine (ranging from 1 = ‘Strongly Disagree’ to 9 = ‘Strongly Agree’). Additionally, internal consistency reliability analysis was used to indicate whether the scale, that consisted of several items, was reliable. The Cronbach’s Alpha (α) was examined, which provided a value of .931 (α = .931). The internal consistency of the scale is reliable when the Cronbach's α is greater than .60 (Malhotra, 2010). Thus, the PFC Scale was highly reliable.

Halfway during the PFC statements, the participants were tested on their level of attention by using an instructional manipulation check (IMC). The IMC was established by Oppenheimer, Meyvis and Davidenko (2009) in order to measure whether participants read the instructions. Thus, it indirectly measures satisficing, which people engage in if they choose the “first minimally acceptable alternative that comes to mind” (p. 867) instead of making an attempt to find the optimal solution for a problem (Oppenheimer et al., 2009). The IMC is an embedded question within the survey which is equal to the other questions in length and response format, but instead of choosing the answer(s) that suit(s), participants are asked to confirm that they have paid attention to the instruction. In the survey of this current research, participants were asked the following: “Please select ‘Slightly Agree’ for this question” on a scale from one to nine (1 = ‘Strongly Disagree, 9 = ‘Strongly Agree’).

It was decided to also measure cultural background in this research, as evidence was found in previous studies that cultural background can also have an influence on illusory pattern perception. It might thus be a confounding variable, which is a variable that obscures the influence of another variable. As such variables can distort research results and evaluation efforts, it is important to control for them (Ewert & Sibthorp, 2009).

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the fundamental relatedness of things. Holistic thinking is also more connected to intuitive thinking, as the authors state that Chinese people seek “intuitive instantaneous understanding through direct perception” (Nisbett et al., 2001, p. 294), and that the Chinese “did not make formal models of the natural world but rather proceeded by intuition and empiricism” (Nisbett et al., 2001, p. 293).

As already stated in section 2.4 of this research, Walker et al. (2019) have found that, if someone engages in an intuitive thinking style, which is the opposite of an analytic thinking style, this person is “more likely to endorse illusory patterns as well as irrational beliefs” (Walker et al., 2019, p. 111). Therefore, it was decided to use cultural background as a control variable in this research.

It is expected that people from Eastern cultures are more likely to engage in illusory pattern perception because of their holistic and intuitive way of thinking. For this reason, a question regarding cultural background was added to the survey with four answer options: (1) Eastern, (2) Western, (3) Prefer not to say, and (4) Other, and a world map was shown that indicated which parts of the world belong to Eastern and Western cultures.

3.3 Procedure

The participants were first shown a disclosure form in which important information was given regarding the study and what to expect: it stated that participation was voluntary, that there was no direct benefit, that no costs were anticipated, and that study-related information would be kept confidential. After this, they were told that the study investigated how consumers experience profoundness, and instructions were given regarding which device to use for filling out the survey, which Internet browser to use, to be complete and honest, to read the questions carefully and to not talk about the study with others.

The participants were then randomly assigned to either the low reliance on feelings condition (reason-based mindset) or the high reliance on feelings condition (feeling-based mindset). Participants in the reason-based mindset condition were told they should describe different situations that really happened to them in which they relied on their reasoning to make a judgment or decision and it was the right thing to do. An example was also given, that stated the following: “I recently have bought a computer and first compared some computers based

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Furthermore, the participants in the feelings-based mindset condition were told they should describe different situations that really happened to them in which they relied on their feelings to make a judgment or a decision and it was the right thing to do. The example given stated the following: “I had a very good feeling toward my new roommate from the moment I

met him. Although objectively we were quite different, my feelings told me that we would be good friends. My feelings were correct! We became best friends after only a week. Trusting how I felt about my new roommate was definitely the right thing to do”. In both conditions, the

participants were required to write a story of at least 50 characters.

After writing the story, the participants were presented with the introductory text to the Snowy Picture Task, explaining that they would see ten ambiguous images, one at a time, that only showed for three seconds each. After each image they were shown the scale on which they had to indicate to what extent they saw a pattern in the image. When participants selected five or higher on the scale, they were asked to indicate what they saw in the picture.

Following the Snowy Pictures Task, the participants were shown an introductory text to the PFC Scale, instructing them to indicate for all 18 PFC statements, and for the attention check, to what extent they agreed with it.

The end of the survey contained demographic questions regarding age, gender, and cultural background, and the participants were asked if they experienced any problems or technical issues, if they participated in a similar study before, and what the purpose of the current survey was. Additionally, a manipulation check was included at the end of the survey to verify whether the manipulation of reliance on feelings really manipulated the construct that was wished to manipulate. One out of the three manipulation check questions created by Martel, Pennycook and Rand (2019, p. 17), was selected, which stated the following: “At the beginning of the survey, you were asked to respond using your:” 1 = Emotion, 2 = Reason”.

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Through Instagram, potential respondents were approached via the researcher’s network and by using the pages of several colleges and universities throughout the Netherlands in order to get Dutch and International students to engage in the experiment. Additionally, as it was decided to use cultural background as a control variable, it had to be ensured to reach an approximately equal amount of people from Western and Eastern cultures. Therefore, Facebook groups with people from Asia as members, and the hashtag ‘Asian’ on Instagram were used to reach potential respondents from Eastern cultures.

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4. Results

4.1 Main Analysis

It was hypothesized that reliance on feelings, compared to reliance on reasoning, leads to an increase in illusory pattern perception (H1). In order to test this hypothesis, negative binomial regression analysis was executed, as the dependent variable was a count variable. Cultural background was also added to the analysis, in order to control for its potential effect on illusory pattern perception. The results are shown in Appendix 6.

The Goodness of Fit model indicates whether the negative binomial distribution fits the data, based upon a goodness-of-fit chi-squared test. The model was not statistically significant (X2(199) = 190.721, p = .958), which means there was no overdispersion. This indicated that the model fitted the data well and analysis could be continued.

Additionally, the Omnibus Test table showed statistical significance (p = .000), which indicated that the fit of the model improved because of adding the predictor variables. Thus, the full model was a significant improvement in fit over a null model with no predictors added, and therefore interpretation of results could be continued.

The Test of Model Effects table showed statistical significance for the reliance on feelings manipulation (b* = .98, SE = .28, p = .001, 95% Confidence Interval [.43, 1.53]), and for cultural background (b* = -.81, SE = .26, p = .002, 95% CI [-1.33, -.29]). This indicated that reliance on feelings is a significant predictor of the number of illusory patterns perceived; thus, H1 is supported. It also indicated that the cultural background indeed has a confounding effect on illusory pattern perception.

Furthermore, the Parameter Estimates table showed an incidence rate ratio (found in the Exp(B) column) of 2.67 (95% CI [1.53, 4.64) for reliance on feelings; thus, 2.67 times more illusory patterns were perceived when it went from category 0 to category 1 (from relying on reasoning to relying on feelings), or [(2.67-1)*100%] 167%.

For cultural background, the table showed an incidence rate ratio of .44 (95% CI [.27, .75]), which means that .44 times, or [(.44-1)*100%] -56% less illusory patterns were perceived when it went from category 0 to category 1 (from Eastern to Western).

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The Goodness of Fit model was not statistically significant (X2_{(197) = 189.523, p =}

.962); thus, there was no overdispersion and the model fitted the data well.

Additionally, the Omnibus Test table showed statistical significance (p = .000). Thus, the full model was a significant improvement in fit over a null model with no predictors added. The Test of Model Effects table showed no statistical significance for the interaction between reliance on feelings and PFC (p = .529); thus, H2 is not supported.

4.2 Additional Analysis

It was also tested whether there was an interaction effect between reliance on feelings and cultural background. The results can be found in Appendix 8.

The Goodness of Fit model was not statistically significant (X2_{(198) = 183.863, p =}

.929); thus, there was no overdispersion.

Additionally, the Omnibus Test table showed statistical significance (p = .000). Thus, the full model was a significant improvement in fit over a null model with no predictor added, and therefore interpretation of results could be continued.

The Test of Model Effects table showed statistical significance for the interaction between reliance on feelings and category 0 of cultural background (b* = 1.52, SE = .41, p = .000, 95% CI [.72, 2.32]). As category 0 consisted of the Eastern participants, this indicates that the joint effect of reliance on feelings and an Eastern cultural background is significantly greater than when they would be separate.

Furthermore, the Parameter Estimates table showed an incidence rate ratio of 4.57 (95% CI [2.05, 10.18]) for the interaction; thus, 4.57 times more illusory patterns were perceived, or [(4.57-1)*100%] 357%, when a participant with an Eastern cultural background relied on feelings, compared to relying on reasoning.

Moreover, in order to verify whether reliance on feelings has an effect on true pattern perception, an additional negative binomial regression analysis was executed with true pattern perception as outcome variable. The results are shown in Appendix 9.

The Goodness of Fit model indicated that the model was not statistically significant,

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5. Discussion

5.1 General Discussion

Research in several areas has indicated that feelings should be included in studying human behavior with regards to consumer decision-making (Kim, et al., 2007). While previous research mostly focused on the positive side of relying on feelings in decision-making and forming judgments, in this research it was hypothesized that it can actually have a negative consequence.

It was expected that, when an individual relies on his/her feelings instead of reasoning, this could lead to illusory pattern perception: it increases likelihood to recognize connections that are actually non-existent, such as the tendency to see imaginary figures, to form superstitious rituals, to recognize false correlations, and to embrace conspiracy beliefs. Through an experiment executed with 202 participants, support was found for this hypothesis.

This result is partly in line with previous literature, as it adds to the findings that feelings function as “a basis for judgments and decisions” and as “a guide for cognitive processing”, that emotional experiences can fortify specific imagined patterns, and that an intuitive thinking style leads to a higher chance of endorsing illusory patterns and irrational beliefs (Storbeck & Clore, 2008; Mattson, 2014; Walker et al., 2019).

Furthermore, it was hypothesized that an individual with PFC as a character trait is even more likely to fall for illusory pattern perception when he or she relies on feelings. However, for this hypothesis, support was not found, as PFC might have been analyzed incorrectly. This is elaborated in section 5.4.

In the analysis, cultural background has been controlled for, as evidence was found in previous literature that people from Eastern cultures would be more likely to engage in illusory pattern perception because of their holistic and intuitive way of thinking. Indeed, a significant confounding effect of cultural background on illusory pattern perception was found: participants from Western cultures perceived less patterns in the illusory pictures than Eastern participants.

5.2 Theoretical Implications

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improved skills in predicting the outcome of future events, potentially faster judgmental responses, more consistent and stable judgmental responses intrapersonally, and judgments more prophetic of the amount and valence of people’s thoughts (Lee et al., 2009; Pham et al., 2012; Pham et al., 2001). However, this current research is the first, or at least one of the first, to suggest a negative consequence of relying on feelings. After an extensive search into the downside of relying on feelings in decision-making and forming judgments, it can be concluded that no research can be found on this topic.

Second, the current research is the first to control for differences in cultural background in researching illusory pattern perception. Thus, this research is the first to indicate that people from Eastern cultures perceive more illusory patterns than Westerners, and that this effect is even stronger in combination with a feelings-based mindset.

Third, this research is also the first to distinguish between illusory and true pattern perception, by indicating that reliance on feelings only increases the number of illusory patterns perceived.

5.3 Managerial Implications

The findings of this research pose several implications for the field of marketing. As Kim et al. (2007) stated that feelings play a central role in the process of decision-making, consumers who rely on their feelings in buying decisions or forming judgments might believe that there is a meaningful and coherent relationship between stimuli, while in fact the stimuli occur through random processes. For example, consumers might perceive false correlations when they rely on their feelings instead of relying on reasoning. This means that marketing efforts (e.g., commercials, advertisements, and campaigns) that evoke affective reactions might lead to consumers perceiving false correlations and seeing imaginary figures. Marketing efforts should be adapted accordingly in order to manipulate consumers into a more analytic, reasoning-based mindset. This is especially important when working mostly with Eastern consumers.

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5.4 Limitations

Firstly, a limitation of this research is the number of pictures used in the Snowy Pictures Task. Originally, the task consists of 24 snowy pictures, of which 12 contain a hidden picture and the other 12 were static (Whitson & Galinsky, 2008). In this research, the number of pictures was adapted to ten, of which five contained a picture and five were static, in order to prevent the survey from becoming too extensive. Ten pictures might have been insufficient: using the original 24 pictures might have been more reliable.

Secondly, the reliance on feelings manipulation did not work for the entire research sample. As discussed in the methodology, a manipulation check was included in the survey to verify whether the manipulation of reliance on feelings really manipulated the construct that should be manipulated. In the current research, the manipulation did not work for 40 participants out of the 202 in total. Consequently, this could have negatively affected the validity of the results of this study.

Thirdly, the use of preference for consistency as a moderator in this research might also be a limitation, as it was found by Pham et al. (2001) that monitoring feelings consciously leads to more consistent judgmental responses intrapersonally. Thus, it might be the case that PFC acts more as a mediator instead of a moderator, and this might be the reason why no support was found for a moderating effect of PFC.

Fourthly, regarding the feelings-based mindset condition, by asking the participants to write about a past situation in which they relied on their feelings, higher-order, more cognitive, processing might have been activated, as cognitive effort was necessary to describe such a situation. This is more related to System 2 thinking, while relying on feelings is in fact related to System 1.

5.5 Directions for Future Research

It might be useful to replicate this study with the original Snowy Pictures Task containing 12 illusory pattern images and 12 true pattern images, instead of a reduced number. This might make the measurement of illusory pattern perception more reliable. Also, future research might use PFC as a mediator instead of as a moderator, in order to test whether PFC is the explaining variable between reliance on feelings and illusory pattern perception.

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not activated. For example, Rotteveel, de Groot, Geutskens, and Phaf (2001) have executed an experiment in which a contrast between conscious and less conscious affective conditions was made. Participants were primed with ideographs that contained optimally (conscious) or sub optimally (less conscious) facial expressions that were either happy or angry. Future research on the topic of reliance on feelings and illusory pattern perception should use an experiment such as the one used by Rotteveel et al.

Furthermore, it would be insightful to further build on this research by studying the direct consequences of illusory pattern perception on consumer buying behavior, the evaluation of products and services, and opinions about brands. Currently, no studies are found on this subject. The results of these studies would be useful in better understanding how consumers can be guided towards certain buying decisions. It is recommended to further investigate this, in order to be able to adapt marketing strategies accordingly. It is then also important to take cultural background into account, as evidence was found that it affects illusory pattern perception, and as an interaction effect was found between reliance on feelings and Eastern cultures.

As this research is the first stating the negative impact of relying on feelings, future research might expand this subject by researching other negative consequences of relying on feelings in consumer decision-making and forming judgments.

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6. Conclusions and Recommendations

The purpose of this research was to show that, instead of the positive consequences stated in previous literature, reliance on feelings in decision-making and forming judgments can also have a negative influence. The results of the analyses indicate that reliance on feelings (compared to reliance on reasoning) increases illusory pattern perception, which means people are more likely to recognize connections that are actually non-existent. Additionally, cultural background has an influence on perceiving illusory patterns. People from Eastern cultures perceive more illusory patterns than people from Western cultures, especially when combined with reliance on feelings. However, support was not found for a positive moderating effect of PFC on the relationship between reliance on feelings and illusory pattern perception.

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Appendices

Appendix 1. Chi-Square Analysis (Cultural Background, Gender, and Age)

Table 1.

Reliance on Feelings * Cultural Background

Value df Asymptotic Significance

(2-sided)

Exact Sig.

(2-sided) Exact Sig. (1-sided)

Pearson Chi-Square .003a ₁ _.958

Continuity Correctionb _.000 ₁ _1.000

Likelihood Ratio .003 1 .958

Fisher’s Exact Test 1.000 .536

Linear-by-Linear Association .003 1 .958

N of Valid Cases 202

a. 0 cells (0.0%) have expected counts less than 5. The minimum expected count is 40.82 b. Computed only for a 2x2 table

Table 2.

Reliance on Feelings * Gender

Value df Asymptotic Significance (2-sided) Exact Sig. (2-sided) Exact Sig. (1-sided) Pearson Chi-Square .006a ₁ _.941 Continuity Correctionb _.000 ₁ _1.000 Likelihood Ratio .006 1 .941

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Table 3.

Reliance on Feelings * Age

Value df Asymptotic Significance (2-sided) Exact Sig. (2-sided) Exact Sig. (1-sided) Pearson Chi-Square .000a ₁ _.997 Continuity Correctionb _.000 ₁ _1.000 Likelihood Ratio .000 1 .997

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Appendix 2. Non-Parametric Chi-Square Analysis One Sample Test

Table 4.

Frequencies

Observed N Expected N Residual

Reason-based 97 101.0 - 4.0

Feelings-based 105 101.0 4.0

Total 202

Table 5.

Test Statistics

Reliance on feelings manipulation

Chi-Square 317a

df 1

Asymp. Sig. .574

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Appendix 3. Cut-Off Points Outliers Calculations

Table 6.

Cut-Off Points Outliers

Condition M SD Calculation Cut-off point

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Appendix 5. Preference for Consistency Scale (Cialdini et al., 1995) 1. I prefer to be around people whose reactions I can anticipate. 2. It is important to me that my actions are consistent with my beliefs.

3. Even if my attitudes and actions seemed consistent with one another to me, it would bother me if they did not seem consistent in the eyes of others.

4. It is important to me that those who know me can predict what I will do. * 5. I want to be described by others as a stable, predictable person. *

6. Admirable people are consistent and predictable.

7. The appearance of consistency is an important part of the image I present to the world. *

8. It bothers me when someone I depend upon is unpredictable. 9. I don’t like to appear as if I am inconsistent.

10. I get uncomfortable when I find my behavior contradicts my beliefs. 11. An important requirement for any friend of mine is personal consistency. * 12. I typically prefer to do things the same way. *

13. I dislike people who are constantly changing their opinions. 14. I want my close friends to be predictable. *

15. It is important to me that others view me as a stable person. * 16. I make an effort to appear consistent to others. *

17. I’m uncomfortable holding two beliefs that are inconsistent. 18. It doesn’t bother me much if my actions are inconsistent. **

_____________________________________________________________________ Note. Items were scored on a scale with the category designations: Strongly Disagree (1), Disagree (2), Somewhat Disagree (3), Slightly Disagree (4), Neither Agree nor Disagree (5), Slightly Agree (6), Somewhat Agree (7), Agree (8), and Strongly Agree (9).

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Appendix 6. Output Negative Binomial Regression Analysis (Main Effect)

Table 7.

Goodness of Fit a

Variable Value df Value/df

Deviance 153.561 199 .772

Scaled Deviance 153.561 199

Pearson Chi-Square 190.721 199 .958

Scaled Pearson Chi-Square 190.721 199

Log Likelihood b _-171.572

Akaike’s Information

Criterion (AIC) 349.143

Finite Sample Corrected AIC (AICC)

349.264 Bayesian Information

Criterion (BIC)

359.068 Consistent AIC (CAIC) 362.068

Dependent Variable: Total number of patterns detected out of 5 illusory pattern pictures

Model: (Intercept), Reliance on feelings manipulation, Control variable a. Information criteria are in smaller-is-better form.

b. The full log likelihood function is displayed and used in computing information criteria.

Table 8.

Omnibus Test a

Likelihood Ratio Chi-Square

df Sig.

24.569 2 .000

Dependent Variable: Total number of patterns detected out of 5 illusory pattern pictures Model: (Intercept), Reliance on feelings manipulation, Control variable

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Table 9.

Test of Model Effects

Type III

Source Wald

Chi-Square df Sig.

(Intercept) 43.473 1 .000

Reliance on Feelings

Manipulation 12.006 1 .001

Control variable 9.449 1 .002

Model: (Intercept), Reliance on feelings manipulation, Control variable

Table 10.

Parameter Estimates

95% Wald Confidence Hypothesis 95% Wald Confidence Interval Test Interval for Exp(B)

Parameter B Std.

Error

Lower Upper Wald Chi- Square

df Sig. Exp(B) Lower Upper

(Intercept) -1.023 .2635 -1.539 -.506 15.059 1 .000 .360 .215 .603 [Reliance on feelings manipulation=1] .980 .2828 .426 1.534 12.006 1 .001 2.664 1.531 4.638 [Reliance on feelings manipulation=0] 0a _. _. _. _. _. _. ₁ _. _. [Control variable=1] -.811 .2638 -1.328 -.294 9.449 1 .002 .444 .265 .745 [Control variable=0] 0a _. _. _. _. _. _. ₁ _. _. (Scale) 1b (Negative binomial) 1b

Dependent Variable: Total number of patterns detected out of 5 illusory pattern pictures Model: (Intercept), Reliance on feelings manipulation, Control variable

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Appendix 7. Output Negative Binomial Regression Analysis (Moderating Effect) Table 11.

Goodness of Fit a

Deviance 152.300 197 .773

Akaike’s Information Criterion (AIC)

351.882 Finite Sample Corrected AIC

(AICC)

352.188 Bayesian Information Criterion

(BIC) 368.424

Consistent AIC (CAIC) 373.424

Dependent Variable: Total number of patterns detected out of 5 illusory pattern pictures Model: (Intercept), Reliance on feelings manipulation, Reliance on

feelings manipulation * Preference for consistency average score, Control variable a. Information criteria are in smaller-is-better form.

Table 12.

Omnibus Test a

df Sig.

25.830 4 .000

Model: (Intercept), Reliance on feelings manipulation, Reliance on feelings manipulation

* Preference for consistency average score, Control variable a. Compares the fitted model against

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Table 13.

Type III

Source Wald

Chi-Square df Sig. (Intercept) .939 1 .332 Reliance on Feelings Manipulation .086 1 .769 Reliance on Feelings Manipulation * Preference for consistency average score

1.273 2 .529

Control variable 9.193 1 .002

Model: (Intercept), Reliance on feelings manipulation, Reliance on feelings manipulation * Preference for consistency average score, Control variable

Table 14

Parameter B Std.

Error Lower Upper Wald Chi- Square

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[Reliance on feelings manipulation=0] * Preference for consistency average score -.176 .1701 -.510 .157 1.076 1 .300 .838 .601 1.170 [Control variable=1] -.802 .2646 -1.321 -.284 9.193 1 .002 .448 .267 .753 [Control variable=0] 0a _. _. _. _. _. _. ₁ _. _. (Scale) 1b (Negative binomial) 1b

Model: (Intercept), Reliance on feelings manipulation, Reliance on feelings manipulation * Preference for consistency average score, Control variable

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Appendix 8. Additional Analysis: Interaction IV*Control Variable Table 15.

Goodness of Fit a

Deviance 149.640 198 .756

Criterion (BIC) 360.455

Model: (Intercept), Reliance on feelings manipulation * Control variable a. Information criteria are in smaller-is-better form.

Table 16.

Omnibus Test a

df Sig.

28.490 3 .000

Dependent Variable: Total number of patterns detected out of 5 illusory pattern pictures Model: (Intercept), Reliance on feelings manipulation * Control variable

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Table 17.

Type III

Source Wald

Chi-Square df Sig. (Intercept) 44.955 1 .000 Reliance on feelings manipulation * Control variable 27.373 3 .000

Model: (Intercept), Reliance on feelings manipulation * Control variable

Table 18

Parameter B Std.

Error

Lower Upper Wald Chi- Square

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(Negative binomial) 1b

Dependent Variable: Total number of patterns detected out of 5 illusory pattern pictures Model: (Intercept), Reliance on feelings manipulation * Control variable

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Appendix 9. Additional Analysis: True Pattern Perception

Table 19.

Goodness of Fit a

Deviance 23.100 200 .115

Criterion (BIC)

957.306

Dependent Variable: Total number of patterns detected out of 5 true pattern pictures

Model: (Intercept), Reliance on feelings manipulation a. Information criteria are in smaller-is-better form.

Table 20.

Omnibus Test a

Likelihood Ratio Chi-Square df Sig.

.425 1 .515

Dependent Variable: Total number of patterns detected out of 5 true pattern pictures

Reliance on Feelings in Information Processing: How Relying on Your Gut Feeling Can Lead to Illusory Pattern Perception